Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add K-Dense-AI/scientific-agent-skills --skill peer-reviewgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/peer-review)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/peer-review"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/peer-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/peer-review"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/peer-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.02842 |
| Opus 5.5 | $0.00026 | $0.01137 |
| Sonnet 5.5 | $0.00013 | $0.00568 |
| Haiku 4.5 | $0.00007 | $0.00284 |
Grade A, and why
peer-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 26d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- peer-review — 100% identical, 22 lines differ
- peer-review — 94% identical, 22 lines differ
- peer-review — 94% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Peer Review
Support an accountable human reviewer with a rigorous, fair, actionable assessment. Treat every unpublished submission and review as confidential.
Mandatory safety boundary
Before reading or analyzing unpublished content:
- Confirm the user is authorized by the publisher, editor, author, or other material owner.
- Check the target venue’s review, confidentiality, co-review, retention, and AI/tool policies.
- Record conflicts, competence limits, requested scope, and specialist-review needs.
- Default to local-only processing.
If authorization is unclear, do not inspect or quote the manuscript. Clarify only the unresolved authorization; existing documented authorization need not be requested again. Until resolved, use only the intake validator or synthetic/public fixtures. Local processing of the manuscript also requires authorization.
Running a bundled CLI locally does not make the surrounding assistant session local. Treat any manuscript content read into a hosted assistant as external processing when evaluating venue policy and authorization.
Never:
- Send unpublished manuscript, supplement, review, or editorial text to an external service without specific publisher/author authorization and venue permission
- Upload confidential content to a public model, search engine, citation service, grammar tool, plagiarism checker, or image service
- Reuse content for training, benchmarking, product improvement, or unrelated research
- Read broad environment state,
.envfiles, API keys, or credentials - Call a network, LLM, or image API from bundled tools
- Invoke another skill or a PDF/image pipeline automatically
- Impersonate an assigned reviewer, editor, journal, funder, or author
- Fabricate manuscript details, review findings, citations, analyses, experiments, reproduction, or an editorial outcome
- Announce a decision that belongs to an editor or panel
Delete local copies and derivatives when policy requires; otherwise retain only what the controlling policy authorizes. Record deletion or retention without copying confidential content into the record.
What ships with it
23 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/citation_references_template.csv 196 B
- assets/claim_evidence_matrix_template.csv 745 B
- assets/reporting_checklist_template.csv 968 B
- assets/reporting_guidelines.json 14 KB
- assets/review_intake_template.json 1.3 KB
- assets/review_scaffold_template.md 3.0 KB
- assets/source_ledger.csv 13 KB
- assets/statistical_reproducibility_template.json 7.1 KB
- assets/study_profile_template.json 197 B
- references/common_issues.md 14 KB
- references/ethical_review_practice.md 12 KB
- references/reporting_standards.md 15 KB
- references/security_validation.md 4.1 KB
- references/statistical_reproducibility.md 11 KB
- references/tool_reference.md 9.4 KB
- scripts/_common.py 14 KB runs code
- scripts/audit_citations.py 6.9 KB runs code
- scripts/audit_statistics_reproducibility.py 10 KB runs code
- scripts/generate_review_scaffold.py 2.6 KB runs code
- scripts/lint_review.py 8.9 KB runs code
- scripts/select_reporting_guidelines.py 13 KB runs code
- scripts/validate_claim_evidence.py 6.9 KB runs code
- scripts/validate_review_intake.py 14 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 26d ago Changed · +5 lines a042ccdc76d3
- 27d ago Changed · +7 lines 2dc3e363fccd
- 1mo ago First seen · 306 lines · 66 tokens per session scan A 3422beafc240
peer-review is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,953 stars, last pushed yesterday), licensed MIT. It adds 66 tokens to every session and 2,842 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with reciprocal hits, genomic context, and gene trees. Use for virus-host gene exchange, endogenous viral elements, or donor direction.
scholion
Second-opinion support for individuals and clinicians, one person's data at a time — genome, laboratory history, prescriptions, wearables. It reads them locally and states what the data cannot support. No data is baked into the skill: everyone supplies their own. Use it when you need to check a physician's…
csag-extraction
Extract a Conditional Scientific Argumentation Graph and grounded Q&A from a manuscript. Use when representing assertions, contexts, evidence links, and inference steps in machine-readable form.
notebooks
Author, run and convert marimo or Jupyter notebooks. Use when delivering an analysis notebook executed end to end with figures embedded.